MSRCN: Multi-task Learning Network for Cell Segmentation and Regression Counting

Author:

Huang Lihua1ORCID,Huang Liqin1ORCID,Yang Mingjing1ORCID

Affiliation:

1. College of Physics and Information Engineering, Fuzhou University, China

Publisher

ACM

Reference27 articles.

1. Impaired natural killer cell counts and cytolytic activity in patients with severe COVID-19

2. Pretransplant bone marrow cellularity and blood count recovery are not associated with relapse or survival risk following allogeneic stem cell transplant for AML in CR

3. K. Simonyan and A. Zisserman . Very deep convolutional networks for large-scale image recognition . In International Conference on Learning Representations , May 2015 . K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In International Conference on Learning Representations, May 2015.

4. Olaf Ronneberger , Philipp Fischer , and Thomas Brox . U-net : Convolutional networks for biomedical image segmentation . In International Conference on Medical image computing and computer-assisted intervention , pages 234– 241 . Springer, 2015. Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. Springer, 2015.

5. Deep Residual Learning for Image Recognition

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